A semi-automatic technique for multitemporal classification of a given crop within a landsat scene

A classification scheme based on temporal characteristics of a given crop is described. The technique in its present form requires one training field representative of the crop under consideration. This training field is used to determine analytically the time behavior of the crop in the LACIE (Large Area Crop Inventory Experiment) segment. A comparison of this crop's temporal profile, generated in each of the Landsat channels, with that of every pixel in the segment is made to decide the category (crop/noncrop) of the pixel. Classification results have been compared with ground truth for 34 sites in the U.S. Corn Belt. This technique has the potential for a more automated method of generating a near-harvest crop inventory from the satellite data in comparison to the inventory method in current use.